scholarly journals Markov Chain Model-Based Optimal Cluster Heads Selection for Wireless Sensor Networks

Sensors ◽  
2017 ◽  
Vol 17 (3) ◽  
pp. 440 ◽  
Author(s):  
Gulnaz Ahmed ◽  
Jianhua Zou ◽  
Xi Zhao ◽  
Mian Sadiq Fareed
Keyword(s):  
Wireless Sensor Networks ◽  
Markov Chain ◽  
Sensor Networks ◽  
Markov Chain Model ◽  
Wireless Sensor ◽  
Chain Model ◽  
Cluster Heads ◽  
Model Based ◽  
Selection For ◽  
Optimal Cluster

scholarly journals A Novel Cooperative ARQ Method for Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Haiyong Wang ◽  
Geng Yang ◽  
Yiran Gu ◽  
Jian Xu ◽  
Zhixin Sun
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Markov Chain Model ◽  
Relay Node ◽  
Wireless Sensor ◽  
System Throughput ◽  
Chain Model ◽  
Channel Fading ◽  
Relay Nodes

In wireless sensor networks, cooperative communication can combat the effects of channel fading by exploiting diversity gain achieved via cooperation communication among the relay nodes. A cooperative automatic retransmission request (ARQ) protocol based on two-relay node selection was proposed in this paper. A novel discrete time Markov chain model in order to analyze the throughput and energy efficiency was built, and system throughput and energy efficiency performance of proposed protocol and traditional ARQ protocol were studied based on such model. The numerical results reveal that the throughput and energy efficiency of the proposed protocol could perform better when compared with the traditional ARQ protocol.

scholarly journals A Model-Based Approach for Adaptable Middleware Evolution in WSN Platforms

2021 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Walter Tiberti ◽  
Dajana Cassioli ◽  
Antinisca Di Marco ◽  
Luigi Pomante ◽  
Marco Santic
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Embedded System ◽  
Operating Systems ◽  
Parallel Evolution ◽  
Wireless Sensor ◽  
New Techniques ◽  
Model Based ◽  
And Performance ◽  
Hardware Platforms

Advances in technology call for a parallel evolution in the software. New techniques are needed to support this dynamism, to track and guide its evolution process. This applies especially in the field of embedded systems, and certainly in Wireless Sensor Networks (WSNs), where hardware platforms and software environments change very quickly. Commonly, operating systems play a key role in the development process of any application. The most used operating system in WSNs is TinyOS, currently at its TinyOS 2.1.2 version. The evolution from TinyOS 1.x and TinyOS 2.x made the applications developed on TinyOS 1.x obsolete. In other words, these applications are not compatible out-of-the-box with TinyOS 2.x and require a porting action. In this paper, we discuss on the porting of embedded system (i.e., Wireless Sensor Networks) applications in response to operating systems’ evolution. In particular, using a model-based approach, we report the porting we did of Agilla, a Mobile-Agent Middleware (MAMW) for WSNs, on TinyOS 2.x, which we refer to as Agilla 2. We also provide a comparative analysis about the characteristics of Agilla 2 versus Agilla. The proposed Agilla 2 is compatible with TinyOS 2.x, has full capabilities and provides new features, as shown by the maintainability and performance measurement presented in this paper. An additional valuable result is the architectural modeling of Agilla and Agilla 2, missing before, which extends its documentation and improves its maintainability.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

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